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Month: July 2014

Convolutional Neural Networks III

July 31, 2014 / 54 Comments

Hey, I’m recently working on my new version of CNN, the updates are as follows: Support 3-channels images; Add Dropout; In conv layers, one can use either 3-channel conv kernels or single-chanel conv kernels (that is to say, whether share weights). Now I’ve finished most of the works, and I’m debugging the code, hope I can release it … [Read more…]

Posted in: Machine Learning Tagged: CNN

Sparse Coding

July 27, 2014 / 8 Comments

INTRODUCTION Sparse coding is one of the very famous unsupervised methods in this decade, it is a dictionary learning process, which target is to find a dictionary that we can use a linear combination of vectors in this dictionary to represent any training input vector. For better capture structures and patterns inherent in the input vectors, … [Read more…]

Posted in: Algorithm, Machine Learning Tagged: Deep Learning, denoising, Machine Learning, sparse coding, Unsupervised Learning

Restricted Boltzmann Machine

July 22, 2014 / 6 Comments

WHAT IS RBM Restricted Boltzmann Machine is one of the special cases of Boltzmann Machine, which restricted all visible-visible connections and hidden-hidden connections, which makes for each hidden unit, it connects to all visible units, and for each visible unit, it connects to all hidden units. Following is a figure which shows the model of RBM.

Posted in: Algorithm, Machine Learning Tagged: Armadillo, Machine Learning, RBM, Restricted Boltzmann Machine

Coarse-to-fine Optical Flow (Lucas & Kanade)

July 3, 2014 / 27 Comments

OPTICAL FLOW We are always interested in finding the movement of objects from videos, optical flow is one of the most famous methods to do this. Optical flow has lots of uses, such as tracking object, camera correction, mosaics and so on. All optical flow methods are based on the following assumptions: Color constancy (brightness … [Read more…]

Posted in: Algorithm, OpenCV Tagged: coarse-to-fine, Horn Schunck, Lucas Kanade, optical flow

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